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Digitisation in manufacturing: Crunching the numbers

A farmer planting crops in a field seems an unlikely herald of the digital revolution. Yet knowing instantly about changes in his routine or the weather can forearm the sprawling industrial complex around him, reaping multi-million dollar savings.

Big promises have been made about big data, large amounts of information that are subjected to sophisticated analysis to draw insights. In the manufacturing sector, there is excited chatter about the power of digitisation – touted as a component of the fourth industrial revolution – where sensors on devices and machines throughout the supply chain provide reams of data to plant operators and managers. So far, it has been used mainly to scan for defects or weaknesses. But the real-time exchange of information could quicken the pace of an industry used to waiting around for inputs and information.

Sensors linked to computing systems could add between US$1.2trn to US$3.7trn in new economic value for factoriesglobally by 2025.

Many sectors have amassed vast troves of data; the question now is what to do with it. According to the McKinsey Global Institute, a think tank, sensors linked to computing systems could add between US$1.2trn to US$3.7trn in new economic value for factories globally by 2025. Currently, however, the sector has captured less than 30% of the potential of data and analytics.

Proactive and productive

More value would come from being proactive. Information from sensors can boost predictability, for example, by identifying component wear ahead of time, enabling managers to schedule repairs and reduce lulls in operation.

“Roughly $2trn of capital expenditure is expected to happen in India in the next decade, in which manufacturing will play a key role. This will put pressure on prices and therefore [increasing] productivity is going to be a huge requirement,” explains Sunil Mathur, CEO of Siemens India, speaking at the Partnership Summit hosted by Andhra Pradesh state and the Confederation of Indian Industry.

The mining sector has embraced digitisation for this purpose, according to Stephen Wood, director general of Western Australia’s department of state development. “In the last decade Western Australia has absorbed US$326bn of investment in the mining sector, a lot of which has gone to building a digital infrastructure,” he said. “Every time operations shut down, you can take that into account and draw up a regular maintenance schedule. Productivity for the sector is a lot greater.”

American multinational Dow Chemical estimates data-driven decisions yield a return on investment of US$1m to US$2m per plant annually by helping plant managers cut the waste of raw materials, adapt quickly to supply changes and reduce unplanned downtime, according to the firm.

Production is better prepared, too. Another chemical producer, Tata Chemicals, uses real-time data from sensors in farmers’ fields to supply the right agricultural inputs for specific conditions. “We’re able to predict crop productivity – the right time to plant and harvest the crop – real-time in our factory,” says R Mukundan, managing director of Tata Chemicals.

Cutting through noise

Unleashing digitisation’s potential, however, means cutting through the noise to discover the insights. Analysing data requires a blend of IT and manufacturing prowess to sift through the information and pinpoint efficiency savings or performance enhancements. China’s lack of a highly sophisticated services sector is one reason why its slice of the global manufacturing pie has plateaued, according to the Asian Development Bank.

Some 1.5m extra data analysts and managers are needed to help make sense of big data in the US alone

Siemens’ Mathur agrees a big challenge is linking up producers with IT and software capabilities: “Increased productivity happens not only through the generation of data from machines. More importantly, it requires people who can analyse that data and convert it into action on the shop floor.” The issue is a global one: some 1.5m extra data analysts and managers are needed to help make sense of big data in the US alone, according to McKinsey.

Other hurdles remain. The whole supply chain, from small and medium-sized enterprises to large manufacturers, needs to upgrade its digital infrastructure to share and interpret information, say experts. And for all digitisation’s promise, not enough work has been done yet to establish rules for the data it spits out, adds Tata Chemicals’ Mukundan. “Data security, data ownership, bandwidth – we need people to look at regulation and the issues related to all the systemic changes we need to make,” he observes.

Still, ironing out these issues can be a big boon for producers around the world. “Industry 4.0 puts the power back in the arms of [producers],” he says. “It is actually a creed that enables us to move forward.”